Understanding the accuracy of statistical haplotype inference with sequence data of known phase

Andrés, Aida M.; Clark, Andrew G.; Shimmin, Lawrence C.; Boerwinkle, Eric; Sing, Charles F.; Hixson, James E.

doi:10.1002/gepi.20185

Cited by 66 publications

(48 citation statements)

References 42 publications

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“…This resulted in up to a 16% increase in the overall r obs as compared with its direct estimate from the simulated haplotypes. There is no fully reliable computational method to infer haplotypes from diploid genotypes (Andrés et al 2007). The related uncertainty will therefore have to be taken into account in the estimates or procedures, making use of computationally phased haplotypes.…”

Section: Datamentioning

confidence: 99%

Fraction of Informative Recombinations: A Heuristic Approach to Analyze Recombination Rates

Lefebvre

Labuda

2008

Genetics

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In this article we present a new heuristic approach (informative recombinations, InfRec) to analyze recombination density at the sequence level. InfRec is intuitive and easy and combines previously developed methods that (i) resolve genotypes into haplotypes, (ii) estimate the minimum number of recombinations, and (iii) evaluate the fraction of informative recombinations. We tested this approach in its sliding-window version on 117 genes from the SeattleSNPs program, resequenced in 24 AfricanAmericans (AAs) and 23 European-Americans (EAs). We obtained population recombination rate estimates (r obs ) of 0.85 and 0.37 kb À1 in AAs and EAs, respectively. Coalescence simulations indicated that these values account for both the recombinations and the gene conversions in the history of the sample. The intensity of r obs varied considerably along the sequence, revealing the presence of recombination hotspots. Overall, we observed $80% of recombinations in one-third and $50% in only 10% of the sequence. InfRec performance, tested on published simulated and additional experimental data sets, was similar to that of other hotspot detection methods. Fast, intuitive, and visual, InfRec is not constrained by sample size limitations. It facilitates understanding data and provides a simple and flexible tool to analyze recombination intensity along the sequence.

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Section: Datamentioning

confidence: 99%

Fraction of Informative Recombinations: A Heuristic Approach to Analyze Recombination Rates

Lefebvre

Labuda

2008

Genetics

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“…Estimation of the frequency of extreme events is often of particular interest, and point frequency analysis using a single set of data is well established. However, uncertainties associated with limited sample size in an "on site" analysis are a well documented problem in existing literature (Andres et al, 2007;Faustini and Kaufmann, 2007).…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal analysis of extreme precipitation regimes across South Korea and its application to regionalization

Lee

Kwon

Kim

2012

Journal of Hydro-environment Research

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“…[2][3][4][5][6][7] The recent advances of sequencing technology have made directly testing rare variants possible. 8,9 Therefore, there is increasing interest to detect associations between rare variants and complex traits.Recently, several statistical methods to detect associations between rare variants and complex traits have been developed for unrelated individuals. These methods can be roughly divided into three groups: burden tests, quadratic tests, and combined tests.…”

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Test of rare variant association based on affected sib-pairs

Sha

Zhang

2014

Eur J Hum Genet

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With the development of sequencing techniques, there is increasing interest to detect associations between rare variants and complex traits. Quite a few statistical methods to detect associations between rare variants and complex traits have been developed for unrelated individuals. Statistical methods for detecting rare variant associations under family-based designs have not received as much attention as methods for unrelated individuals. Recent studies show that rare disease variants will be enriched in family data and thus family-based designs may improve power to detect rare variant associations. In this article, we propose a novel test to test association between the optimally weighted combination of variants and trait of interests for affected sib-pairs. The optimal weights are analytically derived and can be calculated from sampled genotypes and phenotypes. Based on the optimal weights, the proposed method is robust to the directions of the effects of causal variants and is less affected by neutral variants than existing methods are. Our simulation results show that, in all the cases, the proposed method is substantially more powerful than existing methods based on unrelated individuals and existing methods based on affected sib-pairs. INTRODUCTIONRecent studies show that the large number of disease-associated variants identified through genome-wide association studies account for only a small portion of the presumed phenotypic variation. 1 One of the potential sources of missing heritability is the contribution of rare variants. [2][3][4][5][6][7] The recent advances of sequencing technology have made directly testing rare variants possible. 8,9 Therefore, there is increasing interest to detect associations between rare variants and complex traits.Recently, several statistical methods to detect associations between rare variants and complex traits have been developed for unrelated individuals. These methods can be roughly divided into three groups: burden tests, quadratic tests, and combined tests. Burden tests include the cohort allelic sums test, 10 the combined multivariate and collapsing method, 11 the weighted sum statistic (WSS), 12 the variable minor allele frequency (MAF) threshold method, 13 and the cumulative minor-allele test 14 among others. Burden tests implicitly assume that all the rare variants are causal and the directions of the effects are all the same. If these assumptions are true, burden tests can be powerful tests; otherwise, burden tests can perform poorly. [15][16][17][18] Quadratic tests include C-alpha test, 19 sequence kernel association test, 15 and the test for Testing the effects of the Optimally Weighted combination of variants (TOW). 17 Quadratic tests also include adaptive weighting methods 20-24 since, as pointed out by Derkach et al, 18 adaptive weighting methods are operationally similar to quadratic tests. Quadratic tests are robust to the directions of the effects of causal variants and are less affected by neutral variants than burden tests are. If most of the ra...

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Understanding the accuracy of statistical haplotype inference with sequence data of known phase

Cited by 66 publications

References 42 publications

Fraction of Informative Recombinations: A Heuristic Approach to Analyze Recombination Rates

Fraction of Informative Recombinations: A Heuristic Approach to Analyze Recombination Rates

Spatio-temporal analysis of extreme precipitation regimes across South Korea and its application to regionalization

Test of rare variant association based on affected sib-pairs

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